Precision Medicine in Dermatology: From Genomic Profiling in Oncology to Targeted Biologics in Psoriasis

For years, dermatology has become increasingly precise in the therapies it can offer. The harder question is whether we can become just as precise in choosing among them. In this episode of The Spot Check, Jamie Restivo, PA-C, is joined by Brad Glick, DO, MPH, to explore what precision medicine looks like as dermatology begins moving beyond how disease appears on the surface and toward what may be happening biologically underneath it.

Clinicians may have several highly effective treatment classes available in inflammatory disease but still rely heavily on trial and error. Restivo and Dr Glick discuss how molecular and transcriptomic profiling may add another layer of information to the clinical picture, particularly in psoriasis and atopic dermatitis, helping clinicians think more intentionally about which therapeutic class may be the better fit for the individual patient in front of them. Just as important, Dr Glick is clear that these tools do not replace clinical judgment; they sit alongside comorbidities, treatment history, patient preference, access, and everything else that already shapes a treatment decision.

The conversation also gets into what repeated treatment cycling costs. A therapy that does not work means more than another prescription. It can mean months lost, another prior authorization, another conversation about switching, and another round of frustration for both patient and clinician. Dr Glick walks through how objective biomarker data may help narrow that process, from the biologic-naive patient to someone who has already experienced primary or secondary treatment failure, while also giving clinicians additional information to bring into access and payer discussions.

What emerges is a larger change in how inflammatory skin disease may eventually be understood. Rather than stopping at phenotype alone, Dr Glick describes a future in which clinicians increasingly consider both what they see and the underlying biology driving it. The tools are still evolving, and they are not perfect. But the direction is clear: less random selection, more information at the point of care, and a more individualized way of matching patients with the therapies most likely to make sense for them.